Implementation of an Improved Algorithm for Denoising & Enhancement of Underwater Images Using Adaptive Transformation Technique |
Author(s): |
Bhavekar Girish Shrikrushnarao , GHRCEM AMRAVATI; Prof. S. P. Chavate, ASSTT. PROFESSOR, GHRCEM AMRAVATI |
Keywords: |
Underwater Images, Image Denoising, Thresholding, Enhancement, Peak Signal to Noise Ratio. Mean Square Error, Entropy, Correlation |
Abstract |
Underwater image de-noising and enhancement is necessary because of underwater image with low signal to noise ratio, low contrast, and poor image quality, due to that pre-processing is necessary before applying wavelet de-noising. Proposed algorithms used Adaptive wavelet combining adaptive threshold selection with adaptive output of the threshold function for image de-noising and CLAHE for enhancement of de-noised image. Finally the output shows that the proposed method removes noise effectively, also improves Peak Signal to Noise Ratio and better visual appearance, wavelet de-noising with enhancement gives desirable results in terms of Peak Signal to Noise Ratio Due to the advantages of its low entropy, multi-resolution characteristics, removing the correlation and choosing base flexibility, wavelet de-noising method more and more attracts people's attention. |
Other Details |
Paper ID: IJSRDV4I110110 Published in: Volume : 4, Issue : 11 Publication Date: 01/02/2017 Page(s): 650-652 |
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